Augmenting search results with interactive search matrix

ABSTRACT

A computer performs a search. The computer receives a search request including a search term, and determines a plurality of association rules that are each a logical implication that the appearance of the search term follows from the appearance, in a corpus of data, of at least one keyword. The computer generates a search matrix having a plurality of cells, and having axes labeled with a plurality of keywords, wherein at least one cell of the search matrix is associated with an association rule of the plurality of association rules. Based on a cell selection of the search matrix, the computer generates an augmented search string including the search term and at least one keyword of the plurality of association rules.

FIELD OF THE INVENTION

The present invention relates generally to internet search engines, andmore particularly to search engine indexing utilizing term and keyworddetection, subject matter ontologies, and association ruledetermination.

BACKGROUND

The use of the Internet has become pervasive, and business entities andindividuals use the Internet as a tool for obtaining informationregularly. For example, such Internet users use search engines to searchnumerous World Wide Web sites and/or databases for information relevantto search terms. In recent years, the sophistication of search engineshas improved, increasing the ability of search engines to produce searchresults that accurately reflect the search terms provided by the users.However, in circumstances where users are interested in understanding abroad field, such accuracy can actually be counterproductive. Further,search engines typically present users with a large volume of relevantinformation, and the users must consider a large portion of the relevantinformation to comprehensively understand the context of the searchresults.

SUMMARY

Embodiments of the present invention provide for a program product,system, and method in which a computer performs a search. The computerreceives a search request including a search term, and determines aplurality of association rules that are each a logical implication thatthe appearance of the search term follows from the appearance, in acorpus of data, of at least one keyword. The computer generates a searchmatrix having a plurality of cells, and having axes labeled with aplurality of keywords, wherein at least one cell of the search matrix isassociated with an association rule of the plurality of associationrules. Based on a cell selection of the search matrix, the computergenerates an augmented search string including the search term and atleast one keyword of the plurality of association rules.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

FIG. 1 is a block diagram of a search environment in accordance with anembodiment of the present invention.

FIGS. 2A and 2B are illustrations of a user interface depicting a searchmatrix in accordance with an embodiment of the present invention.

FIG. 3 is a flowchart depicting steps followed by a search engine inaccordance with an embodiment of the present invention.

FIG. 4 is a block diagram of a computer system in accordance with anembodiment of the present invention.

DETAILED DESCRIPTION

As will be appreciated by one skilled in the art, aspects of the presentinvention may be embodied as a system, method or computer programproduct. Accordingly, aspects of the present invention may take the formof an entirely hardware embodiment, an entirely software embodiment(including firmware, resident software, micro-code, etc.) or anembodiment combining software and hardware aspects that may allgenerally be referred to herein as a “circuit,” “module” or “system.”Furthermore, aspects of the present invention may take the form of acomputer program product embodied in one or more computer-readablemedium(s) having computer-readable program code embodied thereon.

Any combination of one or more computer-readable medium(s) may beutilized. The computer-readable medium may be a computer-readable signalmedium or a computer-readable storage medium. A computer-readablestorage medium may be, for example, but not limited to, an electronic,magnetic, optical, electromagnetic, infrared, or semiconductor system,apparatus, or device, or any suitable combination of the foregoing. Morespecific examples (a non-exhaustive list) of the computer-readablestorage medium would include the following: an electrical connectionhaving one or more wires, a portable computer diskette, a hard disk, arandom access memory (RAM), a read-only memory (ROM), an erasableprogrammable read-only memory (EPROM or Flash memory), an optical fiber,a portable compact disc read-only memory (CD-ROM), an optical storagedevice, a magnetic storage device, or any suitable combination of theforegoing. In the context of this document, a computer-readable storagemedium may be any tangible medium that can contain, or store a programfor use by or in connection with an instruction execution system,apparatus, or device.

A computer-readable signal medium may include a propagated data signalwith computer-readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electro-magnetic, optical, or any suitable combination thereof. Acomputer-readable signal medium may be any computer-readable medium thatis not a computer-readable storage medium and that can communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus, or device.

Program code embodied on a computer-readable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wireline, optical fiber cable, RF, etc., or any suitable combination ofthe foregoing.

Computer program code for carrying out operations for aspects of thepresent invention may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as Java (note: the term(s) Java may be subject to trademark and/orservice mark rights in various jurisdictions throughout the world, and,to that extent, references to this term(s) herein are to be taken toexclusively apply only to legitimate products of the trademark/servicemark owner(s)), Smalltalk, C++ or the like and conventional proceduralprogramming languages, such as the “C” programming language or similarprogramming languages. The program code may execute entirely on theuser's computer, partly on the user's computer, as a stand-alonesoftware package, partly on the user's computer and partly on a remotecomputer or entirely on the remote computer or server. In the latterscenario, the remote computer may be connected to the user's computerthrough any type of network, including a local area network (LAN) or awide area network (WAN), or the connection may be made to an externalcomputer (for example, through the Internet using an Internet ServiceProvider).

Aspects of the present invention are described below with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems) and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer program instructions. These computer program instructions maybe provided to a processor (i.e., a computing processor) of a generalpurpose computer, special purpose computer, or other programmable dataprocessing apparatus to produce a machine, such that the instructions,which execute via the processor of the computer or other programmabledata processing apparatus, create means for implementing thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

These computer program instructions may also be stored in acomputer-readable medium that can direct a computer, other programmabledata processing apparatus, or other devices to function in a particularmanner, such that the instructions stored in the computer-readablemedium produce an article of manufacture including instructions whichimplement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer,other programmable data processing apparatus, or other devices to causea series of operational steps to be performed on the computer, otherprogrammable apparatus or other devices to produce a computerimplemented process such that the instructions which execute on thecomputer or other programmable apparatus provide processes forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

Referring now to FIG. 1, a block diagram of search environment 100 inaccordance with an embodiment of the present invention is shown. Searchenvironment 100 includes network 110, user computer 120, servers 130,and search engine 140. Network 110 can be, for example, a local areanetwork (LAN), a wide area network (WAN) such as the Internet, or acombination of the two, and can include wired or wireless connections.In general, network 110 can be any combination of connections andprotocols that will support communications between user computer 120,servers 130, and search engine 140 in accordance with an embodiment ofthe invention. As will be discussed in detail below, person 102, a userof search environment 100, can utilize user computer 120 to search for asearch term using search engine 140, and to interact with a resultingsearch matrix, generated by search engine 140, on user interface 104 ofuser computer 120.

In various embodiments, user computer 120, each one of servers 130, aswell as search engine 140, can include a laptop, tablet, or netbookpersonal computer, a desktop computer, a personal digital assistant, asmart phone, a mainframe computer, or a networked server computer.Further, user computer 120, each one of servers 130, as well as searchengine 140, can include computing systems utilizing clustered computersand components to act as single pools of seamless resources whenaccessed through network 110, or can represent one or more cloudcomputing datacenters. In general, user computer 120, each one ofservers 130, as well as search engine 140, can be any programmableelectronic device as described in further detail below with respect toFIG. 4.

User computer 120 includes software, such as a web browser program, forinteracting with search engine 140, and optionally with one or more ofservers 130, via network 110. For example, one or more of servers 130can host web pages viewable on the web browser program of user computer120. For another example, the web browser program of user computer 120can load a search interface web page from search program 148 of searchengine 140, in order to make a search request. In particular, person 102can enter a search term into the loaded search interface web pagedisplayed by the web browser program, and the web browser program canmake a search request by transmitting the search term back to searchprogram 148. Subsequently, search program 148 can generate a searchmatrix (e.g., search matrix 260 depicted in FIG. 2A, etc.) and transmitthe search matrix to user computer 120 as discussed in detail below.Additionally, person 102 can interact with the search matrix to selectone or more cells for augmented searching, as further discussed indetail below.

Search engine 140 includes crawler program 142, parser program 144,indexer program 146, search program 148, and search data 150. Searchprogram 148 provides an interface between search engine 140 and clientsof search engine 140 (e.g., one or both of person 102 and user computer120 can be regarded as clients of search engine 140, etc.). For example,search program 148 can provide an interface by transmitting a searchinterface web page to a web browser program of user computer 120, andthen by interacting with person 102 via the search interface web page.Search program 148 also generates a search matrix, and assists person102 in interacting with the search matrix to select one or more cellsfor augmented searching, by utilizing a subject-matter ontology storedin search data 150, as well as by utilizing data that has been stored insearch data 150 by crawler program 142, parser program 144, and indexerprogram 146.

Crawler program 142, parser program 144, and indexer program 146 operatetogether to crawl, parse, and index web pages hosted on servers 130, tofacilitate the handling of search requests by search program 148. Theoperation of crawler program 142, parser program 144, and indexerprogram 146 can occur continuously, as background processes, such thatsearch requests received by search program 148 are handled usingup-to-date information from ongoing crawl, parse, and index operations.Up-to-date information from the operation of crawler program 142, parserprogram 144, and indexer program 146 is stored in search data 150 andaccessible by search program 148.

During operation, crawler program 142 locates web pages hosted onservers 130, fetches the web pages to search engine 140, and providesthe web pages to parser program 144 and indexer program 146 for parsingand indexing, respectively. Crawler program 142 can crawl web pageslinked together with URLs by, for example, starting with a list of seedURLs, crawling the seed URLs, and adding any found URLs to the list forfurther crawling. In various embodiments, crawler program 142 is notlimited to crawling web pages hosted on servers 130, but can also crawlany kind of documents, data stores, or repositories hosted on servers130 and available for crawling by search engine 140.

As crawler program 142 crawls web pages hosted on servers 130, crawlerprogram 142 provides the web pages to parser program 144. Parser program144 includes the subprograms term program 152, keyword program 154, andassociation rule program 156. During operation, term program 152performs search term parsing of each web page, so that indexer program146 can then construct a term index stored in search data 150. Inparticular, term program 152 can tokenize the contents of each web pageprovided by crawler program 142, and provide the tokenized contents toindexer program 146 for the construction of a reverse term index. Areverse term index lists each web page that a given term appears in, tofacilitate basic handling of search requests, as known in the art. Forexample, using the term index in search data 150, search program 148 canhandle a search request by looking up the search term of the searchrequest in the term index to find out which web pages the search termappears in, and by returning these web pages to user computer 120 as abasic search result. As will be discussed in detail below, the operationof keyword program 154 and association rule program 156 significantlyaugment such basic search request handling.

During operation, keyword program 154 performs keyword parsing of eachweb page that parser program 144 receives from crawler program 142, sothat indexer program 146 can then construct a keyword index stored insearch data 150. In particular, keyword program 154 can tokenize thecontents of each web page provided by crawler program 142, identifykeywords, and provide the tokenized keywords to indexer program 146 forthe construction of a reverse keyword index, listing each web page thata given keyword appears in. In one embodiment, keyword program 154operates on each web page in isolation, while in another embodimentkeyword program 154 operates on a large corpus of multiple web pagesduring, e.g., a global analysis phase. Keyword program 154 identifieskeyword tokens by, for example, utilizing keyword extraction techniquessuch as those described in or referenced in Kaur et al., “EffectiveApproaches for Extraction of Keywords,” IJCSI International Journal ofComputer Science Issues, Vol. 7, Issue 6, November 2010; ISSN (online):1694-0814; pp. 144-148, which is herein incorporated by reference in itsentirety. Notably, the contents of the resulting keyword index may be asubset of the contents of the term index described above, becausekeyword program 154 is more selective in making an identification thanterm program 152. Stated another way, a keyword is likely to also be aterm, but a term is not as likely to also be a keyword, althoughexceptions to this rule may be found in certain embodiments.

During operation, association rule program 156 extracts associationrules from each web page that parser program 144 receives from crawlerprogram 142, and stores the association rules in a rule index stored insearch data 150. In one embodiment, association rule program 156 alsodetermines and stores the strength of each extracted association rule.Association rule program 156 typically operates on a large corpus ofmultiple web pages during, e.g., a global analysis phase. Each extractedassociation rule takes the form of a logical implication that theappearance of a keyword follows from the appearance of at least twoother related keywords, i.e., takes the form {keyword 1, keyword 2}

{keyword 3}. Association rule program 156 extracts association rules anddetermines association rule strength by, for example, utilizingassociation rule extraction techniques such as those described in orreferenced in Mahgoub et al., “A Text Mining Technique Using AssociationRules Extraction,” International Journal of Information and MathematicalSciences, 4:1 2008, pp. 21-28, which is herein incorporated by referencein its entirety. In one embodiment, association rule strength isdetermined by the support, confidence, or conviction of an associationrule. Thus, association rule program 156 extracts association rulesamongst the keywords identified by keyword program 154, and stores theextracted association rules and their strengths in a rule index crossreferenced against the keyword index of search data 150.

As discussed above, during operation, crawler program 142 locates webpages hosted on servers 130, fetches the web pages to search engine 140,and provides the web pages to parser program 144 and indexer program 146for parsing and indexing, respectively. During such operation, termprogram 152, keyword program 154, and association rule program 156populate a term index, keyword index, and rule index stored in searchdata 150. As stated above, such operation can occur continuously, asbackground processes, such that search requests received by searchprogram 148 are handled using up-to-date information from ongoing crawl,parse, and index operations, as well as by using a subject-matterontology stored in search data 150. Below, the handling of a searchrequest received by search program 148 will be discussed.

During operation, search program 148 receives search requests from,e.g., user computer 120. For each search request, search program 148generates a search matrix, and assists with user interaction with thesearch matrix to select one or more cells for augmented searching, byutilizing the term index, keyword index, rule index, and subject-matterontology stored in search data 150. In particular, upon receiving asearch request, search program 148 looks up the search term of thesearch request in the subject matter ontology, to identifyontologically-related terms. A search term can be a word, a phrase, or astring including conjunctively and disjunctively joined words orphrases, for example.

For example, if the search term is “mobile phone,” then thesubject-matter ontology can identify “location-based services,”“camera,” “touch screen,” and additional ontologically-related terms.Additional ontologically-related terms of this example are discussed inthe context of FIG. 2A, below. Notably, the subject-matter ontology canactually include multiple, potentially-overlapping ontologies fordifferent subject-matter areas. For example, “mobile phone” might shareontologically-related terms with “tablet computing.” In variousembodiments, the multiple ontologies can have varying scope. Forexample, in one embodiment, search data 150 includes a subject-matterontology limited to a technology scope, such that it includes ontologiesfor electrical devices and digital computers but not, say, medicalconditions. In other embodiments, search data 150 includessubject-matter ontologies dedicated strictly to legal concepts, toautomobile data, or to medical data. Still further, in anotherembodiment search data 150 includes subject-matter ontologies of broad,encyclopedic scope, so that search program 148 can generate a searchmatrix, and assist with user interaction with the search matrix toselect one or more cells for augmented searching, in any conceivablesubject-matter area.

Having looked up the search term of the search request in the subjectmatter ontology to identify ontologically-related terms, search program148 generates a search matrix by utilizing the ontologically-relatedterms to label axes of the search matrix. An exemplary search matrix,search matrix 260, is shown in FIG. 2A to which discussion now turns.

Referring now to FIG. 2A, an illustration of user interface 104depicting search matrix 260 in accordance with an embodiment of thepresent invention is shown. Search matrix 260 is a two-axis matrix, andeach axis is labeled with keywords 1 through n, eachontologically-related to a search term of a search request received bysearch program 148. Only keywords 1 through 4, and n, are shown forclarity. In one embodiment, keywords 1 through 3 are “location-basedservices,” “camera,” and “touch screen” in accordance with an exampledescribed above. It should be understood that n, an integer, can be anynumber of ontologically-related terms found by search program 148 duringa look-up of the search term in the subject matter ontology. Withinsearch matrix 260 are a number (e.g., n²) of row-column cells. Searchprogram 148 shades, leaves unshaded, or fills with the text “n/a” eachrow-column cell, as discussed below. FIG. 2A further depicts userselections 262 and 264, also discussed below.

Search program 148 generates search matrix 260 by labeling the axes withkeywords 1 through n, by filling in the same-keyword row-column cells onthe diagonal of search matrix 260 with “n/a,” and by filling in (e.g.,shading, etc.) each dissimilar-keyword row-column cell according towhether or not the keywords intersecting at the cell imply the searchterm of the search request, according to an association rule stored inthe rules index of search data 150. For example, search program 148fills in the cell of keyword 1 and keyword 1 with “n/a,” as well as thecell of keyword 2 and keyword 2, etc., proceeding through the cell ofkeyword n and keyword n. Further, search program 148 shades the cell ofkeyword 1 and keyword 2, shades the cell of keyword 1 and keyword 3, andleaves unshaded the cell of keyword 1 and keyword 4. In one embodiment,the intensity of the shading is governed by the strength of the relevantassociation rule. For example, the cell of keyword 1 and keyword 2 canbe shaded lightly if those keywords imply the search term weakly, whilethe cell of keyword 1 and keyword 3 can be shaded darkly if thosekeywords imply the search term of the search request strongly. Inanother embodiment, cells will be shaded at all only if theirintersecting keywords imply the search term with a strength exceeding auser threshold.

Notably, the shading of cells in search matrix 260 is the sameregardless of whether cells are named by row-column intersection or bycolumn-row intersection; i.e., search matrix 260 is reflectedidentically across the “n/a” diagonal. This is the case because,according to the operation of a given association rule, the statement{keyword 1, keyword 2}

{search term} is equivalent to the statement {keyword 2, keyword 1}

{search term}.

Having received a search request including a search term, and havingthen generated search matrix 260 based on the search term, searchprogram 148 transmits search matrix 260 to user computer 120, where itis displayed to person 102 on user interface 104. It should beunderstood that in one embodiment, the visual depiction of search matrix260 depicted in FIG. 2A is generated client-side, at user computer 120,such that search program 148 does not actually generate a graphicaldepiction, and instead generates and transmits only a data structuresufficient for user computer 120 to generate the visual depiction ofsearch matrix 260. Person 102 can then interact with search matrix 260to select one or more cells for augmented searching.

Person 102 can select one or more cells for augmented searching by, forexample, selecting one or more cells with a mouse or other pointingdevice. The selection is transmitted from user computer 102 to searchprogram 148. Upon receiving a selection of a single cell, for exampleuser selection 262, search program 148 generates an augmented searchstring including the search term in the original search request, as wellas the keywords intersecting at the selected cell. For example, userselection 262 selects the cell at the intersection of keyword 2 andkeyword n, and as such search program 148 generates an augmented searchstring “search term AND (keyword 2 AND keyword n).” Notably, theaugmented search string includes the search term, conjunctively joinedwith both keywords, themselves also conjunctively joined.

Further, upon receiving a selection of multiple cells, for example userselection 264, search program 148 generates an augmented search stringincluding the search term in the original search request, as well as thekeywords intersecting at all of the selected cells. For example, userselection 264 selects the cells at the intersections of keyword 2,keyword 3, and keyword 4. As such, search program 148 generates anaugmented search string “search term AND ((keyword 2 AND keyword 3) OR(keyword 2 AND keyword 4)).” Notably, the augmented search stringincludes the search term conjunctively joined with disjunctively joinedsets of conjunctively joined keywords. In particular, in the augmentedsearch string, keyword 2 is conjunctively joined with each of keyword 3and keyword 4, in two disjunctive sets. Another selection of multiplecells (not shown) can be made by, for example, selecting an axis labelto automatically select all of the cells in the label's row or column(e.g., selecting the keyword 2 column label will have the effect ofselecting both cells of user selection 264, as well as all of theadditional cells in the same column).

Having generated an augmented search string including the search term inthe original search request, as well as the keywords intersecting at theone or more selected cells, search program 148 performs a search usingdata in search data 150 to return an augmented search result to usercomputer 120. For example, search program 148 can perform a search bylocating web pages that include that include the logical combination ofsearch terms and keywords in the augmented search string in the termindex of search data 150. Having located such relevant web pages, searchprogram 148 returns them to user computer 120 as an augmented searchresult, which person 102 can view.

Referring now to FIG. 2B, an illustration of user interface 104depicting search matrix 261 in accordance with an embodiment of thepresent invention is shown. Search matrix 261 is similar in most regardsto search matrix 260, except that search program 148 has not filled inthe same-keyword row-column cells on the diagonal of search matrix 260with “n/a.” Instead, search program 148 has filled in (e.g., withshading, etc.) every row-column cell according to whether or not thekeywords intersecting at the cell imply the search term of the searchrequest, according to an association rule stored in the rules index ofsearch data 150. Notably, in this embodiment each extracted associationrule can take the form of a logical implication that the appearance of akeyword follows from the appearance of at least one other relatedkeyword, e.g., can take the form {keyword 2}

{search term}. As such, in the context of FIG. 2B, search program 148can generate an augmented search string including the search term in theoriginal search request, as well as the single keyword intersecting at aselected cell on the diagonal of search matrix 261.

Referring now to FIG. 3, flowchart 302 depicts steps followed by searchengine 140 in accordance with an embodiment of the present invention. Instep 310, crawler program 142 crawls servers 130 to fetch web pages. Instep 312, term program 152 of parser program 144 parses the web pages toextract terms to construct a term index in search data 150. In step 314,keyword program 154 of parser program 144 parses the web pages toextract keywords to construct a keyword index in search data 150. Instep 316, association rule program 156 of parser program 144 extractsassociation rules and determine their strengths to construct a ruleindex in search data 150.

In step 318, search program 148 receives a search request including asearch term from user computer 120. In step 320, search program 148looks up the search term in a subject-matter ontology in search data 150to identify ontologically-related terms of the search term. In step 322,search program 148 generates a search matrix, such as search matrix 260or search matrix 261, and transmits the generated search matrix to usercomputer 120. In step 324, search program 148 receives a cell selectionof one or more cells of the generated search matrix from user computer120. In step 326, search program 148 generates an augmented searchstring based on the cell selection, and performs a search to generate anaugmented search result. In step 328, search program 148 transmits theaugmented search result to user computer 120.

Referring now to FIG. 4, a block diagram of a computer system inaccordance with an embodiment of the present invention is shown.Computer system 400 is only one example of a suitable computer systemand is not intended to suggest any limitation as to the scope of use orfunctionality of embodiments of the invention described herein.Regardless, computer system 400 is capable of being implemented and/orperforming any of the functionality set forth hereinabove.

In computer system 400 there is computer 412, which is operational withnumerous other general purpose or special purpose computing systemenvironments or configurations. Examples of well-known computingsystems, environments, and/or configurations that may be suitable foruse with computer 412 include, but are not limited to, personal computersystems, server computer systems, thin clients, thick clients, handheldor laptop devices, multiprocessor systems, microprocessor-based systems,set top boxes, programmable consumer electronics, network PCs,minicomputer systems, mainframe computer systems, and distributed cloudcomputing environments that include any of the above systems or devices,and the like. User computer 120, each one of servers 130, as well assearch engine 140, can include or can be implemented as an instance ofcomputer 412.

Computer 412 may be described in the general context of computer systemexecutable instructions, such as program modules, being executed by acomputer system. Generally, program modules may include routines,programs, objects, components, logic, data structures, and so on thatperform particular tasks or implement particular abstract data types.Computer 412 may be practiced in distributed cloud computingenvironments where tasks are performed by remote processing devices thatare linked through a communications network. In a distributed cloudcomputing environment, program modules may be located in both local andremote computer system storage media including memory storage devices.

As further shown in FIG. 4, computer 412 in computer system 400 is shownin the form of a general-purpose computing device. The components ofcomputer 412 may include, but are not limited to, one or more processorsor processing units 416, memory 428, and bus 418 that couples varioussystem components including memory 428 to processing unit 416.

Bus 418 represents one or more of any of several types of busstructures, including a memory bus or memory controller, a peripheralbus, an accelerated graphics port, and a processor or local bus usingany of a variety of bus architectures. By way of example, and notlimitation, such architectures include Industry Standard Architecture(ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA)bus, Video Electronics Standards Association (VESA) local bus, andPeripheral Component Interconnect (PCI) bus.

Computer 412 typically includes a variety of computer system readablemedia. Such media may be any available media that is accessible bycomputer 412, and includes both volatile and non-volatile media, andremovable and non-removable media.

Memory 428 can include computer system readable media in the form ofvolatile memory, such as random access memory (RAM) 430 and/or cache432. Computer 412 may further include other removable/non-removable,volatile/non-volatile computer system storage media. By way of exampleonly, storage system 434 can be provided for reading from and writing toa non-removable, non-volatile magnetic media (not shown and typicallycalled a “hard drive”). Although not shown, a magnetic disk drive forreading from and writing to a removable, non-volatile magnetic disk(e.g., a “floppy disk”), and an optical disk drive for reading from orwriting to a removable, non-volatile optical disk such as a CD-ROM,DVD-ROM or other optical media can be provided. In such instances, eachcan be connected to bus 418 by one or more data media interfaces. Aswill be further depicted and described below, memory 428 may include atleast one program product having a set (e.g., at least one) of programmodules that are configured to carry out the functions of embodiments ofthe invention.

Program 440, having one or more program modules 442, may be stored inmemory 428 by way of example, and not limitation, as well as anoperating system, one or more application programs, other programmodules, and program data. Each of the operating system, one or moreapplication programs, other program modules, and program data or somecombination thereof, may include an implementation of a networkingenvironment. Program modules 442 generally carry out the functionsand/or methodologies of embodiments of the invention as describedherein. Crawler program 142, parser program 144, indexer program 146,search program 148, term program 152, keyword program 154, andassociation rule program 156 can be implemented as or can be an instanceof program 440.

Computer 412 may also communicate with one or more external devices 414such as a keyboard, a pointing device, or one or more devices thatenable a user to interact with computer 412, such as via user interface104 on display 424; and/or any devices (e.g., network card, modem, etc.)that enable computer 412 to communicate with one or more other computingdevices. Such communication can occur via Input/Output (I/O) interfaces422. Still yet, computer 412 can communicate with one or more networkssuch as a local area network (LAN), a general wide area network (WAN),and/or a public network (e.g., the Internet) via network adapter 420. Asdepicted, network adapter 420 communicates with the other components ofcomputer 412 via bus 418. It should be understood that although notshown, other hardware and/or software components could be used inconjunction with computer 412. Examples, include, but are not limitedto: microcode, device drivers, redundant processing units, external diskdrive arrays, RAID systems, tape drives, and data archival storagesystems, etc.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof code, which comprises one or more executable instructions forimplementing the specified logical function(s). It should also be notedthat, in some alternative implementations, the functions noted in theblock may occur out of the order noted in the Figures. For example, twoblocks shown in succession may, in fact, be executed substantiallyconcurrently, or the blocks may sometimes be executed in the reverseorder, depending upon the functionality involved. It will also be notedthat each block of the block diagrams and/or flowchart illustration, andcombinations of blocks in the block diagrams and/or flowchartillustration, can be implemented by special purpose hardware-basedsystems that perform the specified functions or acts, or combinations ofspecial purpose hardware and computer instructions.

What is claimed is:
 1. A method for performing a search, the methodcomprising: receiving, by at least one computing processor, a searchrequest including a search term; determining, by the at least onecomputing processor, a plurality of association rules that are each alogical implication that an appearance of the search term follows froman appearance, in a corpus of data, of one or two keywords that areontologically related to the search term; generating, by the at leastone computing processor, a search matrix having a plurality of cells,and having axes labeled with a plurality of keywords that areontologically related to the search term, wherein at least two cells ofthe search matrix are associated with respective association rules ofthe plurality of association rules; receiving, by the at least onecomputing processor, a cell selection that includes multiple cells ofthe search matrix; generating, by the at least one computing processor,an augmented search string including the search term and, for each cellincluded in the cell selection, at least one keyword of the associationrule of the respectively corresponding cell; and performing, by the atleast one computing processor, a search using the augmented searchstring.
 2. The method of claim 1, wherein the cell selection is receivedfrom a source of the search request.
 3. The method of claim 2, furthercomprising, prior to receiving the cell selection from the source of thesearch request, transmitting, by the at least one computing processor,the search matrix to the source of the search request.
 4. The method ofclaim 3, wherein the source of the search request is a human user. 5.The method of claim 1, wherein determining the plurality of associationrules includes looking up the search term in a subject-matter ontologyto identify at least one keyword that is ontologically related to thesearch term.
 6. The method of claim 1, wherein, in the augmented searchstring, the search term is conjunctively joined with the at least onekeyword of the association rule for each respectively corresponding cellin the cell selection.
 7. A computer program product for performing asearch, the computer program product comprising: one or morecomputer-readable storage devices and program instructions stored on atleast one of the one or more computer-readable storage devices, theprogram instructions comprising: program instructions to receive asearch request including a search term; program instructions todetermine a plurality of association rules that are each a logicalimplication that an appearance of the search term follows from anappearance, in a corpus of data, of one or two keywords that areontologically related to the search term; program instructions togenerate a search matrix having a plurality of cells, and having axeslabeled with a plurality of keywords that are ontologically related tothe search term, wherein at least two cells of the search matrix areassociated with respective association rules of the plurality ofassociation rules; program instructions to receive a cell selection thatincludes multiple cells of the search matrix; program instructions togenerate an augmented search string including the search term and, foreach cell included in the cell selection, at least one keyword of theassociation rule of the respectively corresponding cell; and programinstructions to perform a search using the augmented search string. 8.The computer program product of claim 7, wherein the cell selection isreceived from a source of the search request.
 9. The computer programproduct of claim 8, further comprising program instructions to, prior toreceiving the cell selection from the source of the search request,transmit the search matrix to the source of the search request.
 10. Thecomputer program product of claim 9, wherein the source of the searchrequest is a human user.
 11. The computer program product of claim 7,wherein determining the plurality of association rules includes lookingup the search term in a subject-matter ontology to identify at least onekeyword that is ontologically related to the search term.
 12. Thecomputer program product of claim 7, wherein, in the augmented searchstring, the search term is conjunctively joined with the at least onekeyword of the association rule for each respectively corresponding cellin the cell selection.
 13. A system for performing a search, the systemcomprising: one or more processors, one or more memories, one or morecomputer-readable storage devices, and program instructions stored on atleast one of the one or more computer-readable storage devices forexecution by at least one of the one or more processors via at least oneof the one or more memories, the program instructions comprising:program instructions to receive a search request including a searchterm; program instructions to determine a plurality of association rulesthat are each a logical implication that an appearance of the searchterm follows from an appearance, in a corpus of data, of one or twokeywords that are ontologically related to the search term; programinstructions to generate a search matrix having a plurality of cells,and having axes labeled with a plurality of keywords that areontologically related to the search term, wherein at least two cells ofthe search matrix are associated with respective association rules ofthe plurality of association rules; program instructions to receive acell selection that includes multiple cells of the search matrix;program instructions to generate an augmented search string includingthe search term and, for each cell included in the cell selection, atleast one keyword of the association rule of the respectivelycorresponding cell; and program instructions to perform a search usingthe augmented search string.
 14. The system of claim 13, wherein thecell selection is received from a source of the search request.
 15. Thesystem of claim 14, further comprising program instructions to, prior toreceiving the cell selection from the source of the search request,transmit the search matrix to the source of the search request.
 16. Thesystem of claim 15, wherein the source of the search request is a humanuser.
 17. The system of claim 13, wherein determining the plurality ofassociation rules includes looking up the search term in asubject-matter ontology to identify at least one keyword that isontologically related to the search term.